Engineering Manager Jobs

About the team ​​Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats to global security that could scale to an extreme level of severity. Our work involves: Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework , and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. About the role Models are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world. As we push toward AGI, cybersecurity becomes one of the most important and urgent frontiers: the same systems that can accelerate productivity can also accelerate exploitation. As a Researcher for cybersecurity risks, you will help design and implement an end-to-end mitigation stack to reduce severe cyber misuse across OpenAI’s products. This role requires strong technical depth and close cross-functional collaboration to ensure safeguards are enforceable, scalable, and effective. You’ll contribute directly to building protections that remain robust as products, model capabilities, and attacker behaviors evolve. In this role, you will: Design and implement mitigation components for model-enabled cybersecurity misuse—spanning prevention, monitoring, detection, and enforcement—under the guidance of senior technical and risk leadership. Integrate safeguards across product surfaces in partnership with product and engineering teams, helping ensure protections are consistent, low-latency, and scale with usage and new model capabilities. Evaluate technical trade-offs within the cybersecurity risk domain (coverage, latency, model util

About the Team OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. The Industrial Compute team is central to this mission, setting the core infra strategy and implementing this vision. From site selection to the buildout process, this team sits at the intersection of commercial, technical, strategy, and operations, interacting with teams and executives inside and outside of OpenAI. About the Role The Clean Energy and New Technology Lead will own infrastructure clean energy and emerging energy technology strategy and execution, identifying and deploying scalable solutions that enable resilient, low-carbon compute and data center growth. The role will work closely with regulatory and policy teams to align infrastructure expansion with OpenAI’s long-term environmental and operational objectives. This is an individual contributor lead role and does not have direct reports initially. The role will evaluate where emerging energy technologies can materially improve reliability, cost, carbon, speed, or resilience; translate those options into practical deployment pathways; and help ensure OpenAI’s infrastructure growth remains aligned with sustainability considerations. Key Responsibilities Evaluate emerging energy solutions such as clean firm power, advanced storage, grid flexibility, low-carbon backup power, heat reuse, water-related energy efficiency, and other scalable technologies where relevant. Identify pilot opportunities and deployment pathways that can move promising energy technologies from concept to commercially and operationally credible execution. Translate technical options into clear reliability, cost, schedule, carbon, regulatory, and operational implications for infrastructure decision-making. Partner with energy regulatory, policy, procurement, engineering, deployment, finance, legal, and site-readiness teams to align technology and sustainability choices with

About the Team OpenAI’s API Platform organization builds the products and infrastructure that help first-party and third-party developers build with OpenAI models. We ship the API primitives, tools, SDKs, documentation, playgrounds, and platform experiences that make OpenAI’s capabilities reliable, understandable, and useful in production. The API Experience team is focused on the end-to-end developer experience for the OpenAI API. We own the surfaces developers touch every day: docs, SDKs, the Playground, examples, onboarding flows, and the systems that help developers go from first request to production deployment quickly and confidently. About the Role We’re looking for full stack and frontend engineers to help define and build the next generation of OpenAI’s developer experience. In this role, you’ll work across frontend product surfaces, backend systems, SDK and documentation pipelines, and API workflows that serve millions of developers and companies. You’ll partner closely with product, design, research, API engineering, and developer-facing teams to make complex AI capabilities simple to understand, easy to test, and safe to launch in real-world applications. This is a highly cross-functional role for someone who cares deeply about craft, developer empathy, reliability, and product velocity. In this role, you will: Build and scale developer-facing products including the OpenAI API Playground, documentation experiences, onboarding flows, examples, and API workflow tools. Own full stack projects end to end, from product definition and UX collaboration through backend implementation, launch, measurement, and iteration. Improve the systems that generate, maintain, and publish SDKs, API references, docs, guides, and developer examples. Partner with API, research, design, and infrastructure teams to bring new model capabilities and API primitives to developers in a clear, usable way. Use developer feedback, product analytics, and direct customer insight to identif

About the Team The ChatGPT organization at OpenAI supports our mission by bringing advanced AI capabilities to hundreds of millions of users worldwide. The Image Generation team is responsible for one of the fastest-growing experiences in ChatGPT, enabling users to create, edit, and transform images through natural language. Recent breakthroughs in multimodal AI have dramatically improved image quality, instruction following, editing precision, consistency, and text rendering. We're building the systems and experiences that turn these research advances into products used daily by creators, professionals, businesses, and consumers around the world. Our team sits at the intersection of research, product, design, and infrastructure. We work closely with model researchers, mobile engineers, frontend engineers, and platform teams to build intuitive experiences and scalable systems that power image generation at global scale. Whether users are creating marketing assets, visualizing ideas, editing photos, designing products, or simply exploring their creativity, our goal is to make visual creation feel as natural as having a conversation. About the Role We are looking for an experienced Full Stack Engineer to join the Image Generation team and help shape the future of AI-powered visual creation. In this role, you'll own features end-to-end across both frontend and backend systems, building the experiences that enable users to generate, edit, organize, and interact with images inside ChatGPT. You'll work across the entire stack—from highly interactive user interfaces and real-time workflows to backend services, APIs, orchestration systems, and data infrastructure. This role is ideal for engineers who enjoy moving fluidly between product development and systems engineering, collaborating closely with design, product, and research teams to rapidly bring new AI capabilities to users. You'll help define entirely new interaction paradigms as multimodal AI continues to evolve. In

About the Team OpenAI, in close collaboration with our capital partners, is building the world's most advanced AI infrastructure ecosystem. The Scaling Analytics team serves as the data backbone for this effort, enabling leaders and operators to make informed decisions across infrastructure deployment, hardware operations, supply chain, capacity planning, and site execution. As OpenAI’s Industrial Compute expands across an increasing number of global data center campuses, the complexity of managing infrastructure capacity, hardware health, supply flows, and operational performance continues to grow. Scaling Analytics develops the data models, pipelines, metrics, and reporting systems that transform fragmented operational data into actionable insights, helping OpenAI operate infrastructure at unprecedented scale. About the Role We are seeking a Data Engineer to help build and scale the analytical foundations that power OpenAI's infrastructure organization. This individual will partner closely with Hardware Operations, Capacity Planning, Supply Chain, Infrastructure Delivery, Finance, and Engineering teams to create reliable data products that support critical operational and strategic decisions. Today, much of the team's expertise is concentrated within several highly specialized domains including hardware health, GPU attribution, and supply analytics. As Stargate grows and new sites come online, the demand for analytics support continues to expand across both existing and emerging problem spaces. This role will increase the team's ability to move quickly, reduce operational bottlenecks, and provide additional depth across critical infrastructure analytics functions. The ideal candidate combines strong data engineering fundamentals with an ability to navigate ambiguous operational environments, translating complex infrastructure problems into scalable data solutions that improve visibility, decision-making, and execution. Key Responsibilities Design, build, and maint

About the Team The Cloud Agents team builds product infrastructure for long-running agents in the cloud: orchestration, sandboxing and isolation, secure environment connectivity, secrets and identity, observability, reliability, and cost controls. These agents securely connect to diverse developer and customer environments and use tools to accomplish goals. We partner closely with product, research, and infrastructure teams to turn agentic capabilities into dependable platforms for OpenAI products and developers building on OpenAI. About the Role We are looking for an experienced software engineer to help build and scale our cloud agent platform. You will design and operate systems for orchestrating agents at scale. You will work closely with product engineers on ChatGPT, API, and Codex to define the right abstractions and enable them to ship products quickly. Strong backend or infrastructure experience is important; experience with Python, Rust, distributed systems, cloud infrastructure, or product platforms is especially helpful. In this role, you will: Design and scale the orchestration, sandboxing and storage systems that run agentic workloads for Codex, ChatGPT, and the OpenAI API. Partner with product engineers to build a platform that enables them to ship quickly and turn feedback into robust abstractions. Improve reliability, security, performance, and cost efficiency for long-running agents. Deploy services that can operate across different environments and clouds. Your background might look something like: 9+ years of professional engineering experience, excluding internships, in relevant roles at technology and product-driven companies. Experience leading large-scale backend, platform, or infrastructure projects from ambiguous problem statements to production systems. Proficiency in one or more backend languages such as Python, Go, Rust, TypeScript, or similar, and the ability to move across service, platform, and product boundaries. Strong understanding

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, meas

About the Team OpenAI’s Safety teams work to ensure our products are safe, trusted, and resilient as frontier AI systems scale globally. We tackle some of the company’s most important challenges across understanding and preventing misuse and misalignment, intercepting fraud and abuse, and protecting vulnerable users. We are hiring Data Scientists to help build the analytical foundations that allow OpenAI to deploy increasingly capable AI responsibly. We are hiring Data Scientists across several teams that contribute to safety in different ways, including: Safety Systems Integrity Product Policy This is a high-impact role operating at the intersection of product, safety, policy, and research. About the Role As a Data Scientist, Safety, you will help solve complex and ambiguous problems where rigorous analysis directly informs critical decisions. Depending on your background and team alignment, you may work on areas such as: Measure harmful or abusive behavior across OpenAI’s products Detect fraud, manipulation, coordinated misuse Evaluate and improve safety classifiers, rules systems, mitigation systems, and human review workflows Design experiments and causal analyses to understand product, policy, and mitigation impacts Build prevalence estimators, dashboards, monitoring systems, and executive decision frameworks Diagnose gaps in safety and integrity systems using behavioral and product data, and help quantify and navigate false positive / false negative tradeoffs Translate ambiguous safety risks into measurable problems and evidence-based recommendations Partner with Product, Engineering, Policy, Research, and Operations teams to improve safety outcomes Build zero-to-one analytical systems in rapidly evolving domains Ideal Candidate We’re looking for strong Data Scientists who thrive in ambiguous, high-leverage environments. You may be a fit if you have: Strong statistical reasoning and analytical judgment Experience with experimentation, causal inference, or obse

About the Team Business Systems / Enterprise Platform Technology builds the internal systems, data foundations, workflow infrastructure, and enterprise platforms that help OpenAI operate at scale. The EPT AI Pod builds AI-native internal apps, MCP connectors, multi-agent workflows, and reusable platform capabilities across Finance, People, and GTM. About the Role As an Enterprise Applied AI Engineer, you will build internal apps for enterprise operations and the shared platform components those apps run on. This includes MCP connectors, multi-agent orchestration, data architecture, evals, monitoring, auditability, and governance. We’re looking for a hands-on engineer who is strong in Python, system design, enterprise integrations, data architecture, and applied AI systems. You should be excited to turn ambiguous business workflows into reliable internal products and shared infrastructure. In this role, you will: • Build internal apps for enterprise operations across Finance, People, and GTM • Build MCP connectors and enterprise integrations with strong auth, permissions, idempotency, retries, and rate-limit handling • Design end-to-end multi-agent workflows with tool routing, human approvals, audit trails, and safe action boundaries • Design data architecture for operational AI systems, including ingestion, schemas, quality checks, lineage, and governance • Build evals, monitoring, metrics, and regression tests for agentic workflows • Create reusable infrastructure, patterns, and components that other enterprise teams can build on • Partner with system owners and business owners to turn messy enterprise workflows into reliable internal products You might thrive in this role if you: • Have strong Python engineering skills for backend services, MCP connectors, agent/tool workflows, eval harnesses, and data ingestion jobs • Have strong system design skills across shared infrastructure, app architecture, reliability, and scaling • Have experience building internal apps,

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of this API & power-users team, you will improve the capabilities, reliability, and product fit of OpenAI’s agentic models for power users and API developers. You might design evals from real developer workflows, build training environments around production-like tool use, turn qualitative model failures into training data, evals, or post-training interventions, or drive a behavior improvement from discovery through post-training, integration, and launch. This role is intentionally broad. The strongest candidates are comfortable turning ambiguous model behavior problems into concrete progress, whether that means improving tool use, planning, instruction following, recovery from mistakes, or how models behave in API-based workflows. You should be excited to work across research, engineering, data, evals, and product to make models better at acting in real workflows. You will work closely with researchers, engineers, API/product teams, Codex, infrastructure, and safety/align

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Computer Use, you will teach models to operate computers. You will help train models that can navigate browsers and desktops, use tools and applications, reason through complex workflows, collaborate with users and other agents, and complete long-horizon tasks with reliability and judgment. This work sits at the intersection of frontier model training, product behavior, evaluation, and systems engineering, and will directly shape the computer-use capabilities shipped in OpenAI’s next generation of agents. Currently, our models are the best in the world at this behavior! You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Design and run experiments th

About the Team Our Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. Within Safety Systems, the Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. About the Role If you have a specific expertise or speciality related to this work, please note it in your application via your resume, cover letter or application note. Frontier AI systems are expanding what people can do across domains, creating both enormous opportunities and difficult safety questions: when should a model help, when should it refuse, and how do we make those boundaries clear enough to train, evaluate, and enforce? In this role, you will help define how OpenAI’s models should behave in high-risk or high-ambiguity contexts, such as agentic systems, multimodal systems, user safety, privacy, and other emerging risk domains. This is an ideal role for someone who can move across unfamiliar topics, reason from first principles, and turn ambiguity into practical model behavior. You will work closely with research, engineering, product, preparedness, and operations teams to build policies that are technically grounded, measurable, and responsive to real-world risk. In this role, you will: Design and maintain model policies across safety-relevant domains, including dual-use, agentic, and emerging frontier-risk areas. Translate risk and harm models into clear behavioral specifications, evaluation criteria, grading guidance, and system-level safeguards. Define practical boundaries between beneficial uses of AI and assistance that could materially enable harm, exploitation, misuse, or unsafe outcomes. Build policy artifacts that support model training, evaluation, and deplo

About the Team OpenAI’s mission is to build safe artificial general intelligence (AGI) that benefits all of humanity. Achieving this requires bringing the world’s most exceptional talent under one roof to push the boundaries of what’s possible. Our Research Recruiting team plays a critical role in this effort. We are an embedded part of the research organization—working side by side with our research staff to deeply understand evolving priorities, build trust, and strategically shape the future of OpenAI’s talent. About the Role We are looking for a highly strategic recruiter to work closely with the Head of Research Recruiting on a small set of unusually important, high-touch searches and candidate relationships. This role will focus on exceptional talent who does not move through a standard recruiting process: highly visible researchers, technical leaders, operators, and other special-interest candidates where timing, discretion, market intelligence, and tailored engagement matter as much as process execution. This is not a conventional req-based recruiting role. You will help identify where the market is moving, develop intelligence on top talent and competitor activity, translate that intelligence into action, and orchestrate bespoke recruiting strategies for candidates who require a more nuanced path into OpenAI. You should be able to translate these signals and states into clear, actionable advice for leaders and then make it happen. In this role, you will: Partner directly with the Head of Research Recruiting and research leadership team to define priority talent targets and shape bespoke engagement strategies. Build and maintain deep market intelligence across frontier AI, research, engineering, and adjacent talent ecosystems, including competitor movement, candidate motivations, and relationship context. Proactively identify, map, and cultivate exceptional high-profile talent before there is a formal or standard hiring process attached. Translate weak signa

We’re looking for a Software Engineer to architect and build backend systems that enforce data privacy and automate compliance at scale. You’ll work closely with product, infrastructure, security, and legal teams to embed privacy-by-design into our data and access layers. This is a hands-on, high-impact role for an experienced engineer who is passionate about protecting user data while enabling innovation. What You’ll Do Design, build, and operate backend services that enforce policy-driven data access, lifecycle controls, and privacy protections. Develop distributed authorization and identity-aware enforcement mechanisms integrated directly into data services and control planes. Implement auditability, policy hooks, and enforcement observability to ensure compliance is continuously verifiable. Partner with Security, Legal, and Compliance to convert privacy requirements into scalable technical designs and developer-friendly APIs. Harden data platforms and backend services through schema-level controls and data handling constraints by default. Collaborate with infrastructure teams to ensure consistent enforcement across systems while minimizing duplicated implementations. Contribute patterns, libraries, and education that elevate trustworthy data access patterns across the organization. You Might Thrive in This Role If You Have 5+ years of industry experience building and operating backend or infrastructure systems in production. Strong software engineering fundamentals , with fluency in at least one major programming language (e.g., Python, Go, Rust, C++, Java). Experience with distributed authorization, RBAC/ACL systems, encryption-based access, or policy engines. Familiarity with global privacy regulations and their architectural implications. Ability to influence and collaborate with teams across legal, compliance, product, and engineering. A bias toward practical, impactful solutions that balance privacy protections with product needs. Nice to Have Experience wi

About the Team OpenAI’s Industrial Compute organization is building the infrastructure required to support the next generation of AI at unprecedented scale. Through a combination of strategic partnerships and self-built campuses, we are developing and operating large-scale data center infrastructure across power, cooling, networking, compute, construction, and site operations. The scale and complexity of this infrastructure introduces a broad range of environmental, health, and safety considerations across site development, design, construction, equipment deployment, commissioning, and ongoing operations. EHS is a critical part of how we build infrastructure that is safe, resilient, compliant, and capable of operating at scale. About the Role We are seeking an EHS Lead to establish and drive environmental, health, and safety strategy across OpenAI’s rapidly expanding compute infrastructure portfolio. This role will develop the EHS framework for large-scale data center development and operations, partnering closely with engineering, construction, infrastructure delivery, facilities, operations, security, legal, environmental, and external development partners. The EHS Lead will help ensure that safety and environmental considerations are embedded into projects from early design and site development through construction, commissioning, and operations. The role will establish standards and operating mechanisms, assess and mitigate risks, oversee EHS performance across internal teams and third-party partners, and provide technical leadership on complex or high-consequence safety issues. Success requires the ability to operate strategically while maintaining strong technical depth and executional rigor in fast-moving, highly complex infrastructure environments. In this role, you will: Develop and own EHS strategy, standards, programs, and operating mechanisms across OpenAI’s data center and compute infrastructure portfolio. Establish scalable EHS requirements for site de